KSVM is an R implementation of the Support Vector Regression method (SVR).
Similar to Support Vector Machine (SVM) [1]}, SVR uses a kernel function to send its inputs to a higher-dimensional space where the data is linearly separable by a hyper-plane.
SVR aims to fit this hyper-plane such that the prediction error is within a pre-specified threshold.
For our purposes, KSVM uses the Gaussian kernel with the default parameters.
